Embodiments of the invention relate to a smarter search for an entity.
Entity resolution techniques may be used to determine when two or more entities (e.g., people, buildings, cars, things, other objects, etc.) represent the same physical entity despite having been described differently. Sometimes these techniques are called de-duplication, match/merge, identity resolution, semantic reconciliation, or have other names. For example, a first record containing CustID#1 [Bob Jones at 123 Main Street with a Date of Birth (DOB) of Jun. 21, 1945] is likely to represent the same entity as a second record containing CustID#2 [Bob K Jones at 123 S. Main Street with a DOB of Jun. 21, 1945]. Entity resolution can be used within a single data source to find duplicates, across data sources to determine how disparate transactions relate to one entity, or used both within and across a plurality of data sources at the same time. In a typical search for an entity in an entity resolution system, records for the entity are returned to the user.
In an entity resolution system, there are two techniques to perform a search for an entity. The first technique is to use the resolution technology to perform the search. The second technique is to use a Structured Query Language (SQL) query to perform the search.
Oftentimes, a user performs multiple searches, using both techniques, to find an entity. Users may search, modify the initial search, search again, etc., while changing search techniques (entity resolution search vs. SQL search) between searches.